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Schedule Interview NowMy name is Diego G. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Keras, NumPy, pandas, Django, SciPy, etc.. I hold a degree in Master of Business Administration (MBA), Engineer's degree, Master of Science (MS). Some of the notable projects I’ve worked on include: Black Litterman AlgoTrading Toolset, Project Acqua (Smart Cities for Water Supply). I am based in Vera Cruz, Brazil. I've successfully completed 2 projects while developing at Softaims.
I thrive on project diversity, possessing the adaptability to seamlessly transition between different technical stacks, industries, and team structures. This wide-ranging experience allows me to bring unique perspectives and proven solutions from one domain to another, significantly enhancing the problem-solving process.
I quickly become proficient in new technologies as required, focusing on delivering immediate, high-quality value. At Softaims, I leverage this adaptability to ensure project continuity and success, regardless of the evolving technical landscape.
My work philosophy centers on being a resilient and resourceful team member. I prioritize finding pragmatic, scalable solutions that not only meet the current needs but also provide a flexible foundation for future development and changes.
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Mercado Livre
The following work was developed as part of Masters Thesis on the use of Machine Learning on investment porfolio management. The product of the thesis are a set of tools to be used and deployed on other projects. It is a deployment of Black Litterman Model for portfolio management where the “investor views”, a variable that defines a perspective of market behaviour, are derived using a set of Artificial Neural Networks that monitors market behaviour.
Project Acqua is being developed to monitor the water supply system of a city on the macro region of São Paulo in Brazil. The system collects a variety of data from the water supply system and management processes then transforms it into reliable and accurate indicators of performance from the Internation Water Association and Machine Learning (AI) inisghts. The intelligence is presented in the form of specialized dashboards, as the “Hydric Balance Matrix”, georeferenced analysis tools and specialized machine learning models outputs.
Master of Business Administration (MBA) in Business
2019-01-01-2020-01-01
Engineer's degree in Electrical engineering
2005-01-01-2009-01-01
Master of Science (MS) in Systems engineering
2015-01-01-2019-01-01